Search results for "waveforms"

Functional linear models for the analysis of similarity of waveforms

2018

In seismology methods based on waveform similarity analysis are adopted to identify sequences of events characterized by similar fault mechanism and prop- agation pattern. Seismic waves can be considered as spatially interdependent three dimensional curves depending on time and the waveform similarity analysis can be configured as a functional clustering approach, on the basis of which the member- ship is assessed by the shape of the temporal patterns. For providing qualitative ex- traction of the most important information from the recorded signals we propose an integration of the metadata, related to the waves, as explicative variables of a func- tional linear models. The temporal pattern…

Improvement of Hall Effect Current Transducer Metrological Performances in the Presence of Harmonic Distortion

2010

The performance of Hall effect current transducers (HECTs), under distorted waveform conditions, is usually characterized by means of a frequency response test. In this paper, it was investigated if frequency response is able to correctly evaluate the ratio and the phase errors under distorted conditions. Two HECTs, with the accuracy class level of 1% and 0.5%, respectively, were experimentally characterized under two conditions: 1) sinusoidal excitation with frequencies ranging from 50 to 750 Hz, which is the well-known frequency response test, and 2) nonsinusoidal excitation using fundamental frequency and one harmonic with adjusted amplitude and phase shift. It was found that ratio and p…

Detecting clusters in spatially correlated waveforms

2017

Seismic networks often record signals characterized by similar shapes that provide important information according to their geographic positions. We propose an approach to identify homogeneous clusters of seismic waves, combining analysis of waveforms with metadata and spectrogram information. In waveforms clustering, cross-correlation measures between signals may presents some limitations, so we refer to more recent contributes relating data-depth based clustering analysis. The mechanism for alignment is also an important topic of the analysis: warping (or aligning) procedures identify nuisance effects in phase variation, that, if ignored, may result in a possible loss of information and t…

GLM-based automatic picking of waveforms

2011

Functional Linear Models for the Analysis of Similarity of Waveforms

2023

In seismology methods based on waveform similarity analysis are adopted to identify sequences of events characterized by similar fault mechanism and propagation pattern. Seismic waves can be considered as spatially interdependent, three dimensional curves depending on time and the waveform similarity analysis can be configured as a functional clustering approach, on the basis of which the membership is assessed by the shape of the temporal patterns. For providing qualitative extraction of the most important information from the recorded signals, we propose the use of metadata, related to the waves, as covariates of a functional response regression model. The temporal patterns of this effect…

Clustering of waveforms-data based on FPCA direction

2010

The necessity of nding similar features of waveforms data recorded for earthquakes at di erent time instants is here considered, since eventual similarity between these functions could suggest similar behavior of the source process of the corresponding earthquakes. In this paper we develop a clustering algorithm for curves based on directions de ned by an application of PCA to functional data.

Functional Principal components direction to cluster earthquake waveforms

2010

Looking for curves similarity could be a complex issue characterized by subjective choices related to continuous transformations of observed discrete data (Chiodi, 1989). In this paper we combine the aim of finding clusters from a set of individual curves to the functional nature of data, applying a variant of a k-means algorithm based on the principal component rotation of data. We apply a classical clustering method to rotated data, according to the direction of maximum variance. A k-means clustering algorithm based on PCA rotation of data is proposed, as an alternative to methods that require previous interpolation of data based on splines or linear fitting (Garc´ıa- Escudero and Gordali…

FPCA Algorithm For Waveform Clustering

2011

Similar features between waveform data recorded for earthquakes at different time instants could suggest similar behavior of the source process of the corresponding source seismic process. In this paper we combine the aim of finding clusters from a set of individual waveform curves with the functional nature of data, applying a variant of a k-means algorithm based on the principal component rotation of data. This approach overcome the limitation of the cross-correlation, and represents an alternative to methods based on the interpolation of data by splines or linear fitting.

Effect of Pulse Current Mode on Microstructure, Composition and Corrosion Performance of the Coatings Produced by Plasma Electrolytic Oxidation on AZ…

2019

Plasma electrolytic oxidation (PEO) coatings were grown on AZ31 Mg alloy in a silicate-based electrolyte containing KF using unipolar and bipolar (usual and soft-sparking) waveforms. The coatings were dual-layered consisting of MgO, MgF2 and Mg2SiO4 phases. Surface morphology of the coatings was a net-like (scaffold) containing a micro-pores network, micro-cracks and granules of oxide compounds. Deep pores were observed in the coating produced by unipolar and usual bipolar waveforms. The soft-sparking eliminated the deep pores and produced the lowest porosity in the coatings. It was found that the corrosion performance of the coatings evaluated using EIS in 3.5 wt. % NaCl solution is mostly…

Clustering of waveforms based on FPCA direction

2010

Looking for curves similarity could be a complex issue characterized by subjective choices related to continuous transformations of observed discrete data (Chiodi, 1989). Waveforms correlation techniques have been introduced to charac- terize the degree of seismic event similarity (Menke, 1999) and in facilitating more accurate relative locations within similar event clusters by providing more precise timing of seismic wave (P and S) arrivals (Phillips, 1997). In this paper functional analysis (Ramsey, and Silverman, 2006) is considered to highlight common characteristics of waveforms-data and to summarize these charac- teristics by few components, by applying a variant of a classical clust…